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Abstract It is important to directly characterize the modulus of objects through wearable systems, which can further develop electronic skin and human‐computer interaction. In this work, a modulus sensing system based on a pressure sensor and vibration module is developed. This resistive pressure sensor exhibits good linearity and sensitivity. Combined with the vibration module to adjust the applied stress and strain, the modulus value of the objects can be directly calculated. The modulus sensing system demonstrates excellent modulus monitoring capabilities in the range of 60‒3000 kPa modulus and high linearity. In addition, it is used to detect modulus values for different parts of the human body and integrate a concept eye mask to prevent and monitor migraine. The system shows the potential to be further applied to wearable devices for human health monitoring and disease prevention.

Abstract Objectives To analyze the clinical characteristics and influencing factors of hepatotoxicity in patients with advanced hepatocellular carcinoma (HCC) treated with programmed cell death protein‐1 (PD‐1) inhibitors, and to provide a theoretical basis for the treatment of immune‐related hepatotoxicity in patients with advanced HCC. Methods Retrospective analysis of clinical data of patients with advanced HCC from February 2021 to February 2023, in order to summarize and statistically analyze the influencing factors of immune‐related liver adverse reactions. Results A total of 135 patients met the inclusion criteria, among whom 46 patients experienced varying degrees of immune‐related liver adverse reactions, with an incidence rate of 34.1% (46/135). The time range of immune‐related liver adverse reactions was 3–26 weeks, with a median time of 4 weeks. The age range of immune‐related liver adverse reactions was 34–73 years, with a median age of 62 years. Statistical analysis of the influencing factors and liver adverse reactions showed that age, total bilirubin level, and Child–Pugh (C–P) grading were influencing factors for the occurrence of liver adverse reactions (p

BackgroundExtreme precipitation events are becoming more frequent due to climate change. The present study aimed to explore the impacts of extreme precipitation on hospitalizations for acute aortic dissection (AAD) and to identify susceptible populations and quantify the corresponding disease burden.MethodsThe present study used a distributed lag nonlinear model (DLNM) with a quasi-Poisson function to investigate the association between extreme precipitation (≥95th percentile) and the risk of hospitalizations for AAD from 2015 to 2020 in Shantou, Guangdong Province, China.ResultsThe significant adverse effects of extreme precipitation (relative to no precipitation) on daily AAD hospitalizations lasted from lag 5 [relative risk (RR): 1.0318, 95% confidence interval (CI): 1.0067–1.0575] to lag 9 (RR: 1.0297, 95% CI: 1.0045–1.0555) and reached its maximum at lag 7 (RR: 1.0382, 95% CI: 1.0105–1.0665). Males and older adult individuals (≥60 years) were more susceptible to extreme precipitation. A total of 3.68% (118 cases) of AAD hospitalizations were due to extreme precipitation.ConclusionExtreme precipitation was significantly correlated with AAD hospitalizations. Government departments should actively implement extreme precipitation intervention measures to strengthen the protection of males and the older adult (≥60 years) and effectively reduce AAD hospitalizations.

Autonomous underwater vehicles (AUVs) equipped with online visual inspection systems can detect underwater targets during underwater operations, which is of great significance to subsea exploration. However, the undersea scene has some instinctive challenging problems, such as poor lighting conditions, sediment burial, and marine biofouling mimicry, which makes it difficult for traditional target detection algorithms to achieve online, reliable, and accurate detection of underwater targets. To solve the above issues, this paper proposes a real-time object detection algorithm for underwater targets based on a lightweight convolutional neural network model. To improve the imaging quality of underwater images, contrast limited adaptive histogram equalization with the fused multicolor space (FCLAHE) model is designed to enhance the image quality of underwater targets. Afterwards, a spindle-shaped backbone network is designed. The inverted residual block and group convolutions are used to extract depth features to ensure the target detection accuracy on one hand and to reduce the model parameter volume on the other hand under complex scenarios. Through extensive experiments, the precision, recall, and mAP of the proposed algorithm reached 91.2%, 90.1%, and 88.3%, respectively. It is also noticeable that the proposed method has been integrated into the embedded GPU platform and deployed in the AUV system in the practical scenarios. The average computational time is 0.053s, which satisfies the requirements of real-time object detection.

BackgroundEmerging evidence indicates that air pollutants contribute to the development and progression of gastrointestinal diseases. However, there is scarce evidence of an association with appendicitis in mainland China.MethodsIn this study, Linfen city, one of the most polluted cities in mainland China, was selected as the study site to explore whether air pollutants could affect appendicitis admissions and to identify susceptible populations. Daily data on appendicitis admissions and three principal air pollutants, including inhalable particulate matter (PM10), nitrogen dioxide (NO2), and sulfur dioxide (SO2) were collected in Linfen, China. The impacts of air pollutants on appendicitis were studied by using a generalized additive model (GAM) combined with the quasi-Poisson function. Stratified analyses were also performed by sex, age, and season.ResultsWe observed a positive association between air pollution and appendicitis admissions. For a 10 μg/m3 increase in pollutants at lag01, the corresponding relative risks (RRs) and 95% confidence intervals (95% CIs) were 1.0179 (1.0129–1.0230) for PM10, 1.0236 (1.0184–1.0288) for SO2, and 1.0979 (1.0704–1.1262) for NO2. Males and people aged 21–39 years were more susceptible to air pollutants. Regarding seasons, the effects seemed to be stronger during the cold season, but there was no statistically significant difference between the seasonal groups.ConclusionsOur findings indicated that short-term air pollution exposure was significantly correlated with appendicitis admissions, and active air pollution interventions should be implemented to reduce appendicitis hospitalizations, especially for males and people aged 21–39 years.

Abstract The ability to sense light, heat, and touch is vital for human beings, underpinning the interaction between humans and the environment. To mimic the biological perception system, the sensory system converts external light, heat, and mechanical inputs into electrical signals, then processing and storing the data in digital hardware before providing feedback. However, modern digital sensing‐processing systems based on the von Neumann architecture are facing significant challenges in power consumption and latency due to the unprecedented increase in data size and algorithm complexity. A promising solution is to integrate sensors, memory, and control. Here the “state‐of‐the‐art” fusion systems involved in the sensing of visual, olfactory, tactile, visual signals, and control is reviewed. The challenges in high performance and reliability are also discussed.

This study investigated parental acceptability of COVID-19 vaccination for children under the age of 18 years among Chinese parents who are healthcare workers. A closed online survey among full-time doctors or nurses employed by the five collaborative hospitals who had access to smartphones was conducted. Facilitated by the hospital administrators, prospective participants received an invitation sent by the research team via the existing WeChat/QQ groups to complete an online questionnaire. A total of 2,281 participants completed the survey. This study was a sub-analysis of 1332 participants who had at least one child under the age of 18 years. Among the participants, 44.5% reported that they would likely or very likely to have their children under the age of 18 years take up COVID-19 vaccination in the next six months. After adjusting for significant background characteristics, perceived higher vaccine efficacy, longer protection duration, perceived high/very high chance for China to prevent another wave of COVID-19 outbreak with vaccines in place and willingness to receive a COVID-19 vaccination for themselves were associated with higher parental acceptability of COVID-19 vaccination. At interpersonal level, higher frequency of information exposure through social media and direct interpersonal communication were associated with higher parental acceptability of COVID-19 vaccination, while knowing some people who experienced serious side effects following COVID-19 vaccination were associated with lower parental acceptability of COVID-19 vaccination. Despite their important roles in vaccination promotion, Chinese doctors and nurses showed low parental acceptability of COVID-19 vaccination. Effective health promotion is needed when COVID-19 vaccination become available.

The R-2R resistor ladder is one of the best topologies for implementing compact-sized digital-to-analog converter (DAC) arrays in implantable neuro-stimulators. However, it has a limited resolution and considerable inter-channel variation due to component mismatches. To avoid losing analog information, we present sub-radix-2 DAC implemented by the R-βR resistor ladder in this paper. The digital successive approximation register (DSAR) algorithm corrects the transfer function of DACs based on their actual bit weights. Furthermore, a low-cost in situ adaptive bit-weight calibration (ABC) algorithm drives the analog output error between two DACs to zero by adjusting their bit weights automatically. The simulation results show that the proposed algorithm can calibrate the non-linear transfer function of each DAC and the gain error among multiple channels in the background.

The vascular bundle plays a vital role in photoassimilates transportation in rice. However, the vascular bundle characteristics of basal internode and its relationship with stem assimilates allocation and yield remain unclear. In this study, experiments with four different types of rice varieties subjected to three nitrogen application levels were conducted. The results showed that large vascular bundles (LVB) and small vascular bundles (SVB)-related traits of basal internode exhibited genotypic differences. Indica-japonica hybrid varieties had the highest number of cross sectional areas and phloem areas of LVB and SVB, thus the highest stem nonstructural carbohydrates (NSC) translocation, grain filling percentage and grain yield, followed by indica hybrid varieties and indica conventional varieties, and those were the lowest in japonica conventional varieties. The LVB and SVB related traits were significantly and positively correlated with stem NSC translocation, grain filling percentage and grain yield, respectively These results suggested that improving the characteristics of basal internodes was beneficial to enhance stem NSC translocation and consequently increase grain yield. Nitrogen application increased LVB and SVB related traits. Therefore, varieties with developed vascular bundles of basal internodes and cultivation techniques for improving vascular bundle related traits should be considered as the effective route for increasing grain yield.